Series.rolling()

pandas.Series.rolling

Series.rolling(window, min_periods=None, freq=None, center=False, win_type=None, axis=0)

Provides rolling transformations.

New in version 0.18.0.

Parameters:

window : int

Size of the moving window. This is the number of observations used for calculating the statistic.

min_periods : int, default None

Minimum number of observations in window required to have a value (otherwise result is NA).

freq : string or DateOffset object, optional (default None) (DEPRECATED)

Frequency to conform the data to before computing the statistic. Specified as a frequency string or DateOffset object.

center : boolean, default False

Set the labels at the center of the window.

win_type : string, default None

prove a window type, see the notes below

axis : int, default 0

Returns:

a Window sub-classed for the particular operation

Notes

By default, the result is set to the right edge of the window. This can be changed to the center of the window by setting center=True.

The freq keyword is used to conform time series data to a specified frequency by resampling the data. This is done with the default parameters of resample() (i.e. using the mean).

The recognized window types are:

  • boxcar
  • triang
  • blackman
  • hamming
  • bartlett
  • parzen
  • bohman
  • blackmanharris
  • nuttall
  • barthann
  • kaiser (needs beta)
  • gaussian (needs std)
  • general_gaussian (needs power, width)
  • slepian (needs width).

© 2011–2012 Lambda Foundry, Inc. and PyData Development Team
© 2008–2011 AQR Capital Management, LLC
© 2008–2014 the pandas development team
Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.18.1/generated/pandas.Series.rolling.html

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